The Feasibility of Geographical Origin Discrimination of Lampung Robusta Coffee Using UV-Visible Spectroscopy and Chemometric Methods

Abstract

In this study, UV-visible spectroscopy and partial least squares-discriminant analysis (PLS-DA) method was used to discriminate the origin of Lampung robusta coffee. Total 40 Lampung robusta coffee samples with two origins (Lampung Barat and Tanggamus) were used. Each samples has 1 gram weight and was extracted using hot distilled water. UV-visible spectral data of the all aqueous coffee samples were obtained using a UV-visible spectrometer in transmittance mode in the range of 190-1100 nm. The performance of the developed PLS-DA model was evaluated based on coefficient of determination (R2), root mean square error of calibration (RMSEC), and residual prediction to deviation (RPD). Using Savitzky-Golay 1st derivative and moving average spectra, PLS-DA model was developed with the following results: R2 = 0.97 for calibration and R2 = 0.88 for validation, RMSEC = 0.089421 and RMSECV=0.178384. The performance of prediction was quite good with RMSEP = 0.215303 and RPD = 2.83. This results show that UV-visible spectroscopy and PLS-DA method is a promising analytical method to discriminate geographical origin of Lampung robusta coffee.